Web-gaming and Social Computation

In order to study techno-social systems the mere data mining can be unfit to provide the appropriate experimental tests. A more focused, active and sophisticated approach is required to overcome limitations posed by the data mining approach. Yet, the power of the crowd is crucial but it can be exploited in a more studied way, evoking the power of Social Computation to solve the specific experimental need. And in order to involve a motivated community there are two main approaches. The Citizen Science approach aims directly at the recruitment of people interested in the scientific issue, even if lacking of specific competences. The GWAP (Games With A Purpose) approach points at a more general public attracted by the entertaining value of the task formulation. Thus is crucial that the task have to be reshaped in a catchy and engaging web-game.

Experimental Tribe is a web platform for gaming and social computation. It helps researchers to realize web games/experiments and it let people join, while enjoying, the scientific research. It is powered by the Social Dynamic Team, which has also used it for several web-game shaped experiments.

@article{b,
title = {Awareness and learning in participatory noise sensing},
author = {Martin Becker and Saverio Caminiti and Donato Fiorella and Louise Francis and Pietro Gravino and Mordechai Haklay and Andreas Hotho and Vittorio Loreto and Juergen Mueller and Ferdinando Ricchiuti and Vito D.P. Servedio and Alina Sirbu and Francesca Tria},
url = {http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0081638},
year = {2013},
date = {2013-01-01},
journal = {PLoS ONE},
volume = {8},
pages = {e81638-1--e81638-12},
abstract = {The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.